Automatic Brain Tumor Detection and Classification on MRI Images Using Supervised Machine Learning

Brain tumors are recognized as one of the most serious malignancies in both children and adults. Brain tumors grow aggressively, and if they are not treated correctly, the patient’s odds of survivability are slim. Timely detection of brain lesions is critical. To prolong sufferers’ life expectancy, appropriate treatment planning and precise diagnoses are of paramount importance. Magnetic Resonance Imaging is the most successful tool for detecting tumor cells. The radiologist examines the MRI scans. In light of the intricacies that make up brain tumors and their qualities, the manual inspection might be error prone. To detect cancers at a preliminary phase, an automated brain tumor detection system is necessary. In this project, tumors in brain MRI are spotted using machine learning approaches. The MRI images are processed using a deep learning package called Keras API that offers ways to load, prepare, and process images, and the images are later classified using machine learning algorithms.